Reminders for knitting commands in code chunks - can delete when we’re done
include = FALSE - code is run, but neither code nor results appear in knitted fileecho = FALSE - code not included in knitted file, but results areeval = FALSE - code is not run in the knitted filemessage = FALSE - messages do not appear in knitted filewarning = FALSE - warnings do not appear…fig.cap = "..." - adds a caption to graphical resultsWaste diversion comes with global benefits including a decrease in
global warming potential (GWP). However, waste diversion stands to especially benefit those populations living closest to landfills by decreasing local green house gas emissions and other hazards such as odor, smoke, noise, and
water contamination.This project aims to identify which populations live closest to construction and demolition landfills in North Carolina and therefore which populations stand to benefit the most from waste diversion in the construction industry. The focus on the construction industry was inspired by one of the group member’s master’s project which is focused on circularity and waste diversion in the construction industry.
Are construction and demolition landfills in North Carolina disproportionately
more common in low income counties and/or counties with high minority
populations?
what’s the difference between this and section 2?
########does this also count as table with dataset structure? Meghan askin John on 4/1
| Dataset Names | Relevant Information | Source |
|---|---|---|
| Site Waste Facility | Lists all landfills in NC and includes landfill type and address. | NC DEQ https://deq.nc.gov/about/divisions/waste-management/solid-waste-section/solid-waste-facility-lists-presentations-and-annual-reports/solid-waste-facility-lists |
| CDC Social Vulnerability | Contains estimates of poverty and minority data by county. | Agency for Toxic Substances and Disease Registry https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html |
| USA Counties Shape File | Spatial data frame that will establish the map of NC. | US Census https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html |
| SVI Variable Name | Variable Description |
|---|---|
| E_TOTPOP | Population estimate,2014-2018 ACS |
| E_POV | Persons below poverty estimate,2014-2018 ACS |
| E_MINRTY | Minority (all persons except white, non-Hispanic)estimate,2014-2018 ACS |
#import SVI tract-level data and change FIPS from character to factor
svi2018_nc_tract_st <-st_read('./Data/Spatial/NorthCarolinaTract/SVI2018_NORTHCAROLINA_tract.shp')
## Reading layer `SVI2018_NORTHCAROLINA_tract' from data source
## `Z:\ENV872\ENV872-SeylerHyyppa_Final\Data\Spatial\NorthCarolinaTract\SVI2018_NORTHCAROLINA_tract.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 2192 features and 126 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -84.32187 ymin: 33.84232 xmax: -75.46062 ymax: 36.58812
## Geodetic CRS: NAD83
svi2018_nc_tract_st$FIPS<-as.factor(svi2018_nc_tract_st$FIPS)
mapview(svi2018_nc_tract_st)